Day-to-day variability in resting metabolic rate in strength athletes

Resting Metabolic Rate (RMR) is measured in sport settings for health monitoring and nutrition planning; however, interpreting repeated measures requires an understanding of typical day-to-day variability under habitual, free-living conditions. This study quantified intra-individual variability in RMR among weight-stable strength-trained athletes, examined the impact of data processing approaches, and established protocol-specific least significant change (LSC) thresholds under ecological conditions.

A repeated-measures design was used to quantify intra-individual variability in RMR in 13 weight-stable strength-trained athletes (8 male, 5 female). RMR was measured on five consecutive mornings using the Parvo Medics TrueOne 2400 metabolic cart with a Hans Rudolph mouthpiece under standardized conditions. Breath-by-breath data were processed using multiple cleaning approaches to evaluate their impact on RMR estimates, with the most reliable method retained for analysis. Intra-individual variability was quantified and used to derive protocol-specific LSC thresholds.

Session averaging produced the lowest intra-individual variability in RMR (CV: 3.4 ± 1.4%) compared with alternative data cleaning approaches. Mean RMR was 26.9 ± 1.4 and 29.1 ± 1.7 kcal·kgFFM^-1·day^-1 in males and females, respectively. The group-level LSC was 2.9 ± 1.2 kcal·kgFFM^-1·day^-1 (10.4 ± 4.2%), representing the magnitude of change required to exceed expected within-subject variability under the conditions of this protocol. Fat-free mass (FFM) was positively associated with both absolute RMR and day-to-day variability, whereas prior-day training load and protein intake showed no clear association with RMR variability.

Notable intra-individual variability occurs in repeated RMR measurements in strength-trained athletes under applied conditions. Meaningful interpretation of change requires protocol-specific reliability estimates to distinguish true physiological change from expected day-to-day variation. Session averaging improves measurement consistency and is recommended for mouthpiece-based indirect calorimetry systems. RMR should be interpreted relative to individual and context-specific variability rather than universal thresholds.